Motional Ad LLC

Koninklijke Philips Corporation N.v.

Ayman Alalao

Molly Lara Flexman

Hsun-Hsien Chang

Ashish Panse

Tyler Hendrickson

Shaurya Agarwal

Aleksandra Popovic

Yuechen Qian

Brian David Gross

Merlijn Sevenster

Harshavardhan Ravichandran

Shih-Yuan Liu

John Blair

Yugang Jia

Thomas Andre Forsberg

Eran Rubens

Qianxi Li

Jesse Adam Miller

Alexander Steinwald

Benoit Jean-Dominque Bertrand Maurice Mory

Techniques are disclosed for creating and presenting a graphical user interface for display of autonomous vehicle behaviors. The techniques include determining a trajectory of a vehicle operating in a real-world environment. Sensors of the vehicle obtain sensor data representing an object in the real-world environment. A maneuver of the vehicle to avoid a collision with the object is predicted based on the sensor data and the trajectory of the vehicle. It is determined that a passenger comfort level of a passenger riding in the vehicle will decrease based on the maneuver of the vehicle. The passenger comfort level is measured by passenger sensors of the vehicle. A graphical user interface is generated including representations of the vehicle, the object, and a graphic, text, or a symbol alerting the passenger of the predicted maneuver. The graphical user interface is transmitted to a display device of the vehicle.

Graphical user interface for display of autonomous vehicle behaviors

Among other things, techniques are described for monitoring and controlling autonomous vehicles (AVs). As an example, at least one processor determines that a first AV is in a field of view of a user wearing an augmented reality display device, determines first data regarding an operation of the first AV, and causes at least a portion of the first data to be presented to the user using the augmented reality display device. For example, a graphical user interface is presented in the field of view of the user using the augmented reality display device, and at least the portion of the first data is included on the graphical user interface, such that at least the portion of the first data appears to be arranged spatially proximal to the first AV in the field of view of the user.

Augmented reality enabled autonomous vehicle command center

Among other things, techniques are described for forecasting occupancy of a vehicle location. This includes receiving, by at least one processor, status information of a parking location the status information representing an availability of the parking location; predicting, by the at least one processor, a future status of the parking location based on the received status information; determining, by the at least one processor, a destination based on the predicted future status of the parking location; and providing, by the at least one processor, the predicted future status to a controller of a vehicle for controlling the vehicle to drive to the destination.

Forecasting vehicle location occupancy

Among other things, an apparatus includes a processor, and storage for instructions executable by the processor to, in connection with a trip of a person in an autonomous vehicle, select a specific location at which the person will be picked up for the trip or a specific location at a destination of the trip, and present through a user interface of a device visible information that depicts the specific location.

Augmented reality vehicle interfacing

A mixed reality device () employing a mixed reality display () for visualizing a virtual augmentation of a physical anatomical model, and a mixed reality controller () for controlling a visualization by the mixed reality display () of the virtual augmentation of the physical anatomical model including a mixed reality interaction between the physical anatomical model and a virtual anatomical model. The mixed reality controller () may employ a mixed reality registration module () for controlling a spatial registration between the physical anatomical model within a physical space and the virtual anatomical model within a virtual space, and a mixed reality interaction module for controlling the mixed reality interaction between the physical anatomical model and the virtual anatomical model based on the spatial registration between the physical anatomical model within the physical space and the virtual anatomical model within the virtual space.

Virtual augmentation of anatomical models

An augmented reality system includes a head-mountable augmented reality platform () having a display to provide guidance to a user. A prediction module () is trained in a procedure and is configured to predict a next activity in the procedure based on a current condition. An image generation module () is responsive to the prediction module to provide a visual cue of a predicted next activity to the user through the head-mountable augmented reality platform.

Augmented reality for predictive workflow in an operating room

A patient monitor () includes a display (). Patient values () are obtained for one or more known variables of a risk prediction function (). One or more unknown variables of the risk prediction function are determined, and at least one hyperplane () is defined as values assumable by the one or more unknown variables. Values of the risk prediction function are computed over the at least one hyperplane using the obtained patient values. A visualization template is selected from a database of visualization templates () using template selection indices including the risk prediction function and the one or more unknown variables. Using the visualization template, a visualization () of the computed values of the risk prediction function over the at least one hyperplane is displayed.

Contextualized patient-specific presentation of prediction score information

An autonomous vehicle receives sensor data from one or more sensors of the autonomous vehicle, and generates a request for remote control of the autonomous vehicle by a computer system remote from the autonomous vehicle. Generating the request includes determining a quality metric associated with a network connection between the autonomous vehicle and the computer system, and upon determining that the quality metric is greater than a threshold quality level, transmitting, from the autonomous vehicle to the computer system the request for remote control and a first data item representing the sensor data. The first data item meets one or more conditions associated with the threshold quality level.

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Cambridge, MA, United States of America

Ayman Alalao